ORIGINAL RESEARCH article
Front. Bioinform.
Sec. Network Bioinformatics
Identification and Validation of Tumor Microenvironment-Related Therapeutic Targets in Gastric Cancer Using Integrated Multi-Omics and Molecular Docking Approaches
Provisionally accepted
Mohamed Kalith Oli M1
JAFAR ALI IBRAHIM2*- 1School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, India
- 2School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
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With increased drug resistance and tumor heterogeneity accounting for limited therapeutic strategies, gastric cancer remains one of the major causes of cancer-related mortality around the globe. Targeting the components of the tumor microenvironment (TME) has become a promising therapeutic strategy due to their crucial roles in cancer cell proliferation, progression, and metastasis. One of the limitations of the previously identified therapeutic targets is their limited applicability to a broader patient population. This study aims to identify (TME)-related therapeutic targets using an integrated bioinformatics and molecular docking approach that involves a larger number of datasets to cover a broader cohort of gastric cancer patients. It analyzed multiple publicly available transcriptomic datasets using Robust Rank Aggregation (RRA) meta-analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to identify significant hub genes. Furthermore, protein-protein interaction (PPI) network analyses, conducted using multiple methods such as Cytohubba topology analysis and ClusterONE module analysis, refined the potential therapeutic candidates. Functional enrichment analyses were performed to identify vital genes involved in TME interactions and ECM remodeling. Additionally, the enriched genes were validated for their significant dysregulation in the Cancer Genome Atlas gastric adenocarcinoma dataset (TCGA-STAD), and three independent GEO datasets to ensure differential expression across distinct cohorts. Genes with consistent dysregulation were used in survival analyses across TCGA and two GEO datasets to prioritize hub genes with prognostic significance. Finally, a targeted literature survey ensured the exclusion of previously targeted genes, and molecular docking analyses conducted using phytocompounds identified potential therapeutic leads with strong affinities for the identified targets. This integrated approach revealed notable, promising targets in the TME and natural compounds for developing potential personalized therapeutic strategies in gastric cancer.
Keywords: gastric cancer1, differentially expressed genes2, extracellular matrix3, MolecularDocking4, Therapeutic Targets5, personalized medicine6
Received: 27 Jun 2025; Accepted: 27 Oct 2025.
Copyright: © 2025 M and IBRAHIM. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: JAFAR ALI IBRAHIM, jafarali.s@vit.ac.in
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